Convert a List of Tuples into Dictionary with Grouped Dict Values in Python

Lets say I have a list of tuples like the following

l: list[tuple] = [
    ('bobs trucking', 'ID1'),
    ('bobs trucking', 'ID2'),
    ('bobs trucking', 'ID3'),
    ('bobs groceries', 'ID6'),
    ('bobs groceries', 'ID7'),
    ('bobs groceries', 'ID8'),
    ('bobs groceries', 'ID9')
]

I’d like to group the repeated first tuple elements (e.g. ‘bobs trucking’) into a dictionary with values that have the grouped IDs concatenated like a CSV but for every n values for each item in a list

# An example of how I'd accomplish this (but need a way to do it for every n elements)
l2: list[str] = ['ID1','ID2','ID3']
csv_delim: str = ','.join(l2)

Every unique key has a list where each list item is a CSV string of size n=3

# Desired ultimate result
bobs_stuff: dict = {
    'bobs trucking': ['ID1,ID2,ID3'],
    'bobs groceries': ['ID6,ID7,ID8','ID9']
}

Note: I’d like to do this without Pandas.

>Solution :

Iterate over your list of tuples and populate a dictionary with its contents as follows:

list_of_tuples = [
    ('bobs trucking', 'ID1'),
    ('bobs trucking', 'ID2'),
    ('bobs trucking', 'ID3'),
    ('bobs groceries', 'ID6'),
    ('bobs groceries', 'ID7'),
    ('bobs groceries', 'ID8'),
    ('bobs groceries', 'ID9')
]

bobs_stuff = {}

N = 3
td = {}

for k, v in list_of_tuples:
    td.setdefault(k, []).append(v)

for k, v in td.items():
    for i in range(0, len(td[k]), N):
        bobs_stuff.setdefault(k, []).append(','.join(v[i:i+N]))

print(bobs_stuff)

Output:

{'bobs trucking': ['ID1,ID2,ID3'], 'bobs groceries': ['ID6,ID7,ID8', 'ID9']}